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Quantitative User Experience Researcher

**Ideal candidate will have statistics, SQL, knowledge of UX or HCI and some experience with either R or Python**

** The Area **
Quantitative UX Researchers conduct empirical research using methods from computer science, quantitative social science, statistics, econometrics, and other fields to understand user behavior and extract meaningful patterns from large data sets. They partner with Designers, Product Managers, Engineers, and other stakeholders across the company to improve the user experience and drive product excellence. The research team covers all advertiser-facing products where advertisers create, monitor, manage, and optimize their advertising campaigns.

** The Role **
​As a Quantitative UX Researcher, you combine skills in experimental design, statistical analysis, programming and human-computer interaction to improve the user experience. As a key member of a product team, you work with stakeholders across functions and levels. You solve challenging problems and empower the team to move forward by developing metrics, measuring results and integrating new methodologies into existing systems. You do more than just crunch numbers: through reports and team engagement, you provide a UX perspective on quantitative data to help stakeholders understand their users. Coming up with solutions is only one part of your job. Equally important is to identify and quantify problems, and to embark on new research areas worth exploring through innovative methods. You apply principles of rigorous and ethical research to build and improve products that satisfy users' needs and exceed their expectations.

** Overall Responsibilities **
– Support existing, establish new, prioritize and drive research initiatives to quantify and improve the advertiser user experience.
– Support product development and design and provide confidence in decision making through thorough quantitative insights
– ​Define and measure quantitative UX goals and metrics in collaboration with Designers, Qualitative Researchers, Engineers and Program Managers.
– Examine existing data and product designs to generate hypotheses and plans for high-impact research.
– Develop code and statistical models to understand user experience.
– Drive change by communicating findings to stakeholders in the company. Make research findings convincing and actionable for both research experts and non-experts.
– Facilitate high research impact through data visualization and novel research communication methods.

** Top 3 Daily Responsibilities **
- Plan research: identify research gaps, distil findings from prior research, develop research plans for quantitative or mixed quantitative+qualitative research into user behaviors in the product
- Execute research: conduct statistical analyses to describe user and customer behaviors, using various slicing mechanisms; identify meaningful patterns and correlate signals to provide a coherent research insight
- Communicate research for Impact: transform research findings into recommendations for the design and product management teams; work as a team to improve research deliverables (reports, presentations, posters); use methods of research communication to deliver lasting research artifacts.

** Required Skills **
– Fluency in SQL
– Mastery of R or Python
– MS or PhD degree in Computer Science, Human-Computer Interaction, Psychology, Statistics or a related field.
– 3 years of relevant work experience with User Experience or Human-Computer Interaction teams.
– Expertise in multivariate statistics and the design of experiments.
– Expertise in data visualization techniques and tools.
– Proficiency in programming computational and statistical algorithms for large data sets.
– Track record of demonstrating excellent command of research questions within a given domain, and of technical tools for the analysis of data within that field.
– Track record of communicating with cross-functional stakeholders of varying levels.

** Nice to Have Skills/Not Required **
– Practical experience in research communication to technical and non-technical audiences. This could take various forms: science blogger, data journalist, data visualisation
– Prior experience of working on enterprise products is a plus.
– Prior experience of working in the advertising industry is a plus.